32,239 research outputs found
Jarzynski Equality, Crooks Fluctuation Theorem and the Fluctuation Theorems of Heat for Arbitrary Initial States
By taking full advantage of the dynamic property imposed by the detailed
balance condition, we derive a new refined unified fluctuation theorem (FT) for
general stochastic thermodynamic systems. This FT involves the joint
probability distribution functions of the final phase space point and a
thermodynamic variable. Jarzynski equality, Crooks fluctuation theorem, and the
FTs of heat as well as the trajectory entropy production can be regarded as
special cases of this refined unified FT, and all of them are generalized to
arbitrary initial distributions. We also find that the refined unified FT can
easily reproduce the FTs for processes with the feedback control, due to its
unconventional structure that separates the thermodynamic variable from the
choices of initial distributions. Our result is heuristic for further
understanding of the relations and distinctions between all kinds of FTs, and
might be valuable for studying thermodynamic processes with information
exchange.Comment: 15 pages, 1 tabl
Unsupervised learning of generative topic saliency for person re-identification
(c) 2014. The copyright of this document resides with its authors.
It may be distributed unchanged freely in print or electronic forms.© 2014. The copyright of this document resides with its authors. Existing approaches to person re-identification (re-id) are dominated by supervised learning based methods which focus on learning optimal similarity distance metrics. However, supervised learning based models require a large number of manually labelled pairs of person images across every pair of camera views. This thus limits their ability to scale to large camera networks. To overcome this problem, this paper proposes a novel unsupervised re-id modelling approach by exploring generative probabilistic topic modelling. Given abundant unlabelled data, our topic model learns to simultaneously both (1) discover localised person foreground appearance saliency (salient image patches) that are more informative for re-id matching, and (2) remove busy background clutters surrounding a person. Extensive experiments are carried out to demonstrate that the proposed model outperforms existing unsupervised learning re-id methods with significantly simplified model complexity. In the meantime, it still retains comparable re-id accuracy when compared to the state-of-the-art supervised re-id methods but without any need for pair-wise labelled training data
Thermodynamics of Information Processing Based on Enzyme Kinetics: an Exactly Solvable Model of Information Pump
Motivated by the recent proposed models of the information engine [D. Mandal
and C. Jarzynski, Proc. Natl. Acad. Sci. 109, 11641 (2012)] and the information
refrigerator [D. Mandal, H. T. Quan, and C. Jarzynski, Phys. Rev. Lett. 111,
030602 (2013)], we propose a minimal model of the information pump and the
information eraser based on enzyme kinetics. This device can either pump
molecules against the chemical potential gradient by consuming the information
encoded in the bit stream or (partially) erase the information encoded in the
bit stream by consuming the Gibbs free energy. The dynamics of this model is
solved exactly, and the "phase diagram" of the operation regimes is determined.
The efficiency and the power of the information machine is analyzed. The
validity of the second law of thermodynamics within our model is clarified. Our
model offers a simple paradigm for the investigating of the thermodynamics of
information processing involving the chemical potential in small systems
All-optical Imprinting of Geometric Phases onto Matter Waves
Traditional optical phase imprinting of matter waves is of a dynamical
nature. In this paper we show that both Abelian and non-Abelian geometric
phases can be optically imprinted onto matter waves, yielding a number of
interesting phenomena such as wavepacket re-directing and wavepacket splitting.
In addition to their fundamental interest, our results open up new
opportunities for robust optical control of matter waves.Comment: 5 pages, 2 figures, to appear in Phys. Rev.
Convergence of Adaptive Finite Element Approximations for Nonlinear Eigenvalue Problems
In this paper, we study an adaptive finite element method for a class of a
nonlinear eigenvalue problems that may be of nonconvex energy functional and
consider its applications to quantum chemistry. We prove the convergence of
adaptive finite element approximations and present several numerical examples
of micro-structure of matter calculations that support our theory.Comment: 24 pages, 12 figure
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